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RecKAN: Kolmogorov-Arnold Networks with a Learnable Recursive Polynomial Basis
Kolmogorov--Arnold Networks (KANs) replace the fixed scalar weights of a standard network with learnable univariate functions on each edge, but existing variants still fix the \emph{basis} that those functions are built from: B-splines, Chebyshev polynomials, wavelets, or Jacobi polynomials, and lea
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